D. Villacci

An Integrated Framework for Smart Microgrids Modeling, Monitoring, Control, Communication, and Verification

The microgrid (MG) paradigm is a new concept which is considered as a solution for addressing technical, economical, and environmental issues of modern power systems. The application of MG is the subject of extensive studies and experimental tests. It is recognized that there are a number of technical challenges concerning the operation, monitoring, control, and protection of MGs systems. In this respect, the rapid development of the information and communication technologies (ICTs) has opened the door for feasible and cost-effective solutions allowing more extensive intra- and interutility information exchange, diffusion, and open access to a wide range of real-time information. Consequently, the ICTs could represent a strategic tool in supporting effective MG operation. According to this statement, the paper proposes an advanced framework based on the service-oriented architectures for integrated MG modeling, monitoring, and control. The proposed framework is platform, language, and vendor independent, and thus it is an ideal candidate for an effective integration in existing energy management systems and distribution management systems (EMSs/DMSs).

An adaptive local learning-based methodology for voltage regulation in distribution networks with dispersed generation

This paper proposes a computational architecture for the voltage regulation of distribution networks equipped with dispersed generation systems (DGS). The architecture aims to find an effective solution of the optimal regulation problem by combining a conventional nonlinear programming algorithm with an adaptive local learning technique. The rationale for the approach is that a local learning algorithm can rapidly learn on the basis of a limited amount of historical observations the dependency between the current network state and the optimal asset allocation. This approach provides an approximate and fast alternative to an accurate but slow multiobjective optimization procedure. The experimental results obtained by simulating the regulation policy in the case of a medium-voltage network are very promising

An Affine Arithmetic-Based Methodology for Reliable Power Flow Analysis in the Presence of Data Uncertainty

Power flow studies are typically used to determine the steady state or operating conditions of power systems for specified sets of load and generation values, and is one of the most intensely used tools in power engineering. When the input conditions are uncertain, numerous scenarios need to be analyzed to cover the required range of uncertainty. Under such conditions, reliable solution algorithms that incorporate the effect of data uncertainty into the power flow analysis are required. To address this problem, this paper proposes a new solution methodology based on the use of affine arithmetic, which is an enhanced model for self-validated numerical analysis in which the quantities of interest are represented as affine combinations of certain primitive variables representing the sources of uncertainty in the data or approximations made during the computation. The application of this technique to the power flow problem is explained in detail, and several numerical results are presented and discussed, demonstrating the effectiveness of the proposed methodology, especially in comparison to previously proposed interval arithmetics techniques.

A distributed architecture for online power systems security analysis

Phenomena that can compromise power systems operation need to be carefully analyzed in order to evaluate their impact on the security and reliability levels of the electrical networks. The real-time assessment of the systems security and reliability levels, especially under unforeseen contingencies, is known as online power system security analysis. For complex networks this process requires large computational efforts whereas computation times should be less than a few minutes for the information to be useful. To address this problem a distributed architecture based on the Web is proposed. The architecture integrates a network of remotely controlled units distributed in the most critical sections of the electrical network for fields data acquisition and safety check violations, a distributed solution engine for the online analysis of the system security, and a Web-based interface for graphical synoptic and reporting development. The results obtained from an intensive experimentation demonstrate the validity of the architecture and stimulate the enhancement of the solution engine through the use of a computational grid able to dynamically acquire the needed resources.

Cooperative sensor networks for voltage quality monitoring in smart grids

The paper intends to give a contribution toward the definition of a fully decentralized voltage quality monitoring architecture by proposing the employment of self organizing sensor networks. According to this para-digm each node can assess both the performances of the monitored site, computed by acquiring local information, and the global performances of the monitored grid section, computed by local exchanges of information with its neighbors nodes. Thanks to this feature each node could automatically detect local voltage quality anomalies. Moreover system operator can assess the system voltage quality index for each grid section by inquiring any node of the corresponding sensors network without the need of a central fusion center acquiring and processing all the node acquisitions. This makes the overall monitoring architecture highly scalable, self-organizing and distributed.

The role of learning methods in the dynamic assessment of power components loading capability

The need for dynamic loading of power components in the deregulated electricity market demands reliable assessment models that should be able to predict the thermal behavior when the load exceeds the nameplate value. When assessing network load capability, the hot-spot temperature of the components is known to be the most critical factor. The knowledge of the evolution of the hot-spot temperature during overload conditions is essential to evaluate the loss of insulation life and to evaluate the consequent risks of both technical and economical nature. This paper discusses an innovative grey-box architecture for integrating physical knowledge modeling (a.k.a. white-box) with machine learning techniques (a.k.a. black-box). In particular, we focus on the problem of forecasting the hot-spot temperature of a mineral-oil-immersed transformer. We perform a set of experiments and we compare the predictions obtained by the grey-, white-, and black-box approaches.

Radial Power Flow Tolerance Analysis by Interval Constraint Propagation

Many applications in modern distribution management systems (DMS) need the support of robust and reliable radial power flow analysis. In this connection, although radial power flow solution algorithms are widely proposed in the literature, their application is often complicated by the presence of uncertainties affecting the distribution network operation. The effect of these uncertainties could affect the power flow solution to a considerable extent. A comprehensive tolerance analysis is therefore required in order to incorporate the effect of data uncertainties into power flow analysis. To address this problem, in this paper the employment of interval constraint propagation (ICP) is proposed. ICP is an effective technique for refining enclosures to solutions of nonlinear systems of equations by merging interval mathematic and constraint propagation techniques. Several numerical results are presented and discussed in order to assess the effectiveness of the proposed methodology as an alternative to sampling-based technique, in radial power flow analysis.

Reliability aspects in wind farms design

Wind park design is not a straightforward task because it involves many heterogeneous aspects to handle in integrated and systemic way. Historically, the reliability issue has often been neglected in favor of economic issue in power systems design. By following the modern tendency of the power system literature, the reliability constraints have to be satisfied a priori, for sake of power system security and safety. For this reason, a rationale procedure is developed in the paper for suitably comparing various alternatives, at the aim of identifying the optimal candidate to be realized. In the work, a specific objective function is proposed in order to select the better wind farm configuration. It is constituted by some terms which basically compare the profits related to the economic trading in the deregulated electric market and the costs due to the investment, operation & management and to system unavailability. This objective function is accurately investigated as a function of the turbines number in order to derive the most convenient alternative, this implying also the optimal choice of the single wind generators size. The ranking coming out from this assessment is then compared with that one which establishes a preferability in terms of expected load not supplied (ELNS). A compromise choice, between the best alternatives provided by the two criteria has finally to be adopted. A simple numerical application is reported in the last part of the paper for testing the validity of the proposed approach.

An integrated approach to improve the networks security in presence of high penetration of RES

Worldwide renewable power flows are increasing rapidly because of the fossil fuels depletion and of the environmental issues generated by their massive employment. Although “environmental-friendly”, the grid integration of a high number of not-conventional power plants yields not-negligible effects on power systems operating and on their security. In this scenario the development of adequate methodologies able to assess in advance the grid vulnerability levels becomes a nowadays a duty. In this regard the paper presents an integrated approach to improve the networks security in presence of high penetration of renewable energy sources (RES). Such an approach is specifically developed for grid assets thermally constrained: the applications refer to transmission lines but however the philosophy behind the procedure is very general. The idea is to synergistically use three modules of a Decentralized and Proactive Architecture for Smart Transmission Grids Modelling, Monitoring and Control that will be presented in detail in successive works. The contribution of this paper is hence to present an integrated approach to assess the thermal loadability of transmission lines carrying power flows from areas with high presence of wind farms. The latter can be regarded as only one functionality of the aforementioned architecture for smart transmission systems. More specifically, the first architecture module is devoted to forecast meteorological variables and quantities needed to the other two which respectively quantify the wind farms power flows injected at an end of an overhead transmission line (OHL) and calculate the dynamic rating of the thermally constrained asset. Numerical simulations refer to the a real case study: a wide area in the southern Italy characterized by a huge installation of wind farms and a transmission line which sometimes constitutes a bottleneck to deliver all the potential “green” production. This research project is carried out with the partnership of the Italian Transmission System Operator (TSO), Terna, and of the Italian Aerospace Research Center, CIRA.

Satellite based communication network for large scale power system applications

With the advent of modern day satellite technology, the electric utility industry is exploring opportunities to expand applications that can be served from space-based platforms. Traditionally, in the electric power industry the use of satellite-based technology is seen in many aspects of wide-area management -- weather satellites are used to provide information on demand and to thus, lower the probability of blackouts or brownouts; GPS satellites are used for system control by providing synchronized measurements; and Low Earth Orbiting (LEO) satellites are being investigated for communication of the power system measurements with the desire to improve reliability and provide global coverage with low data latency. These LEO satellites are typically 500 -1500 km above the Earths surface. The integration of satellite technology into power system operations is emerging now due not only to the large coverage area available from space, improvements in satellite reliability, and lower data-latency, but also the advent of lower cost small satellite buses. Today, satellite applications for power systems are an active area of research in such areas as wide area measurement, control, and communication.